One of the most important aspect of molecular and computational biology
is the reconstruction of evolutionary relationships. The area is well
explored after decades of intensive research. Despite this fact there
remains a need for good and efficient algorithms that are capable of
reconstructing the evolutionary relationship in reasonable time.Since
the problem is computationally intractable, exact algorithms are used
only for small groups of species. In the Maximum Parsimony approach the
time of computation grows so fast when number of sequences increases,
that in practice it is possible to find the optimal solution for
instances containing about 20 sequences only. It is this reason that in
practical applications, heuristic methods are used.

In our
laboratory we have developed parallel adaptive memory programming
algorithms based on Maximum Parsimony and some known neighborhood search
methods for phylogenetic tree construction. The proposed algorithms
achieve a superlinear speedup and find solutions of good quality.